A case-oriented web-based training system for breast cancer diagnosis. (March 2018)

• Record Type: Journal Article
• Authors: Huang, Qinghua; Huang, Xianhai; Liu, Longzhong; Lin, Yidi; Long, Xingzhang; Li, Xuelong
• Is Part Of: Computer methods and programs in biomedicine. Volume 156(2018)
• Page Start: 73
• Page End: 83
• Publication Date: 2018-03
• Subjects: Breast ultrasound images -- Medical database -- Web-based training -- Feature scoring -- BI-RADS -- Computer-aided diagnosis; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2017.12.028
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Accurate diagnosis of breast tumor in ultrasound images is important. We collected 1669 breast tumor cases to form the data base. We develop an online training system for doctors to learn and assess BI-RADS features. A CAD subsystem is designed to rank the features and execute the diagnosis. Our system was tested and validated by doctors and interns. Abstract: Background and Objective: Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. We aim to provide a web-based breast ultrasound database for online training inexperienced radiologists and giving computer-assisted diagnostic information for detection and classification of the breast tumor. Methods: We introduce a web database which stores breast ultrasound images from breast cancer patients as well as their diagnostic information. A web-based training system using a feature scoring scheme based on Breast Imaging Reporting and Data System (BI-RADS) US lexicon was designed. A computer-aided diagnosis (CAD) subsystem was developed to assist the radiologists to make scores on the BI-RADS features for an input case. The training system possesses 1669 scored cases, where 412 cases are benign and 1257 cases are malignant. It was tested by 31 users including 12 interns, 11 junior radiologists, and 8 experienced senior radiologists. Results: This online training system automatically creates case-based exercises to train and guide the newly employed or resident radiologists for the diagnosis of breast cancer using breast ultrasound images based on the BI-RADS. After the trainings, the interns and junior radiologists show significant improvement in the diagnosis of the breast tumor with ultrasound imaging ( p -value < .05); meanwhile the senior radiologists show little improvement ( p -value > .05). Conclusions: The online training system can improve the capabilities of early-career radiologists in distinguishing between the benign and malignant lesions and reduce the misdiagnosis of breast cancer in a quick, convenient and effective manner.